Data Scientist - Manufacturing Analytics
Unison Group · Singapore, Singapore
Business Consulting and Services · 11-50 employees
3 h ago
Senior (5-10 yrs)
Contractor
Singapore
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About the role
Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities. Develop and deploy machine learning models for predictive maintenance, process efficiency, and quality improvement.
What they look for
Data Science
Advanced Analytics
Seeq
Time-series analysis
Python
Pandas
NumPy
Scikit-learn
SQL
Machine Learning
Predictive maintenance
Process optimization
Anomaly detection
Statistical modeling
Data engineering
Root-cause analysis
Requirements
Requires 6+ years of experience in Data Science with hands-on experience in industrial or manufacturing environments. Proficiency in Python, SQL, and the Seeq platform for time-series analysis is essential.
Full description
Must-Have Skills / Requirements
- 6+ years of experience in Data Science / Advanced Analytics
- Hands-on experience in manufacturing / industrial / plant environments
- Strong working knowledge of Seeq (industrial analytics platform) for time-series analysis, including both Seeq Workbench and Data Lab (using the seeq spy library).
- Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL
- Strong understanding of:
- Machine Learning (regression, anomaly detection, predictive models)
- Statistical modeling and hypothesis-driven analysis
- Time-series / sensor data analytics
- Experience building and deploying predictive models for:
- Predictive maintenance
- Process optimization
- Quality and yield improvement
- Ability to work with sensor data, process data, and operational datasets
- Strong analytical thinking, troubleshooting, and root-cause analysis capability
Good-to-Have Skills
- Experience in industries such as:
- Oil & Gas, Chemicals, Manufacturing
- Knowledge of MLOps (model deployment, monitoring, pipelines)
- Exposure to optimization techniques for industrial processes
- Exposure to cloud platforms (Azure / AWS / GCP)
- Familiarity with data visualization tools, real-time / streaming data analytics, data engineering (ETL / data pipelines / data lakes)
Roles & Responsibilities
- Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
- Use Seeq platform for:
- Time-series analysis
- Root cause investigation
- Process monitoring and visualization
- Develop and deploy machine learning models for:
- Predictive maintenance
- Process efficiency improvement
- Quality / yield optimization
- Work closely with plant, engineering, and operations teams to understand real-world process issues
- Translate business and operational challenges into data science solutions
- Build and maintain data pipelines, analytical datasets, and workflows
- Monitor, evaluate, and continuously improve model performance in production
- Present actionable insights through dashboards, reports, and stakeholder discussions
- Ensure data quality, reliability, and governance across manufacturing data sources
- Drive adoption of data-driven decision-making across plant operations
